Influencing Factors Identification and Prediction of Noise Annoyance-A Case Study on Substation Noise

被引:7
作者
Di, Guoqing [1 ]
Wang, Yihang [1 ]
Yao, Yao [1 ]
Ma, Jiangang [2 ]
Wu, Jian [2 ]
机构
[1] Zhejiang Univ, Coll Environm & Resource Sci, Hangzhou 310058, Peoples R China
[2] State Grid Shaanxi Elect Power Res Inst, Xian 710054, Peoples R China
关键词
noise annoyance; non-acoustic factors; influence weight; prediction model; substation noise; ROAD-TRAFFIC NOISE; LOW-FREQUENCY NOISE; SENSITIVITY; EXPOSURE;
D O I
10.3390/ijerph19148394
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Noise-induced annoyance is one person's individual adverse reaction to noise. Noise annoyance is an important basis for determining the acceptability of environmental noise exposure and for formulating environmental noise standards. It is influenced by both acoustic and non-acoustic factors. To identify non-acoustic factors significantly influencing noise annoyance, 40 noise samples with a loudness level of 60-90 phon from 500-1000 kV substations were selected in this study. A total of 246 subjects were recruited randomly. Using the assessment scale of noise annoyance specified by ISO 15666-2021, listening tests were conducted. Meanwhile, basic information and noise sensitivity of each subject were obtained through a questionnaire and the Weinstein's noise sensitivity scale. Based on the five non-acoustic indices which were identified in this study and had a significant influence on noise annoyance, a prediction model of annoyance from substation noise was proposed by a stepwise regression. Results showed that the influence weight of acoustic indices in the model accounted for 80% in which the equivalent continuous A-weighted sound pressure level and the sound pressure level above 1/1 octave band of 125 Hz were 65% and 15%, respectively. The influence weight of non-acoustic indices entering the model was 20% in which age, education level, noise sensitivity, income, and noisy degree in the workplace were 8%, 2%, 4%, 4%, and 2%, respectively. The result of this study can provide a basis for factors identification and prediction of noise annoyance.
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页数:14
相关论文
共 34 条
[1]   Annoyance from industrial noise: Indicators for a wide variety of industrial sources [J].
Alayrac, M. ;
Marquis-Favre, C. ;
Viollon, S. ;
Morel, J. ;
Le Nost, G. .
JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA, 2010, 128 (03) :1128-1139
[2]  
[Anonymous], 2021, ISO 15666:2021
[3]   Assessing aircraft noise-induced annoyance around a major German airport and its predictors via telephone survey - The COSMA study [J].
Bartels, Susanne ;
Rooney, Daniel ;
Mueller, Uwe .
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT, 2018, 59 :246-258
[4]   Contributors to Neighbour Noise Annoyance [J].
Benz, Sarah L. ;
Kuhlmann, Julia ;
Schreckenberg, Dirk ;
Wothge, Joerdis .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2021, 18 (15)
[5]   Road traffic noise: self-reported noise annoyance versus GIS modelled road traffic noise exposure [J].
Birk, Matthias ;
Ivina, Olga ;
von Klot, Stephanie ;
Babisch, Wolfgang ;
Heinrich, Joachim .
JOURNAL OF ENVIRONMENTAL MONITORING, 2011, 13 (11) :3237-3245
[6]   Improvement of Zwicker's psychoacoustic annoyance model aiming at tonal noises [J].
Di, Guo-Qing ;
Chen, Xing-Wang ;
Song, Kai ;
Zhou, Bing ;
Pei, Chun-Ming .
APPLIED ACOUSTICS, 2016, 105 :164-170
[7]   Annoyance response to low frequency noise with tonal components: A case study on transformer noise [J].
Di, Guo-Qing ;
Zhou, Xi-Xi ;
Chen, Xing-Wang .
APPLIED ACOUSTICS, 2015, 91 :40-46
[8]   An experiment study on the identification of noise sensitive individuals and the influence of noise sensitivity on perceived annoyance [J].
Di, Guoqing ;
Yao, Yao ;
Chen, Cong ;
Lin, Qinhao ;
Li, Zhengguang .
APPLIED ACOUSTICS, 2022, 185
[9]   An Optimization Study on Listening Experiments to Improve the Comparability of Annoyance Ratings of Noise Samples from Different Experimental Sample Sets [J].
Di, Guoqing ;
Lu, Kuanguang ;
Shi, Xiaofan .
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2018, 15 (03)
[10]  
Dietrich P, 2013, Uncertainties in Acoustical Transfer Functions: Modeling, Measurement and Derivation of Parameters for Airborne and Structure-Borne Sound